Statistical languages may be used to model data, data mining, and/or other uses. Examples of such statistical languages include R, S, Maple™, Mathematica®, MATLAB, matplotlib, Octave, Python™ with Numpy, Python™ with SciPy, or the like. These statistical languages may be used to generate graphical representations of data beyond the capabilities of languages that query a database. The graphical representations may be utilized by a user to verify statistical modeling of data. For example, a graphical representation of a k-means clustering may be generated and visually validated by a user. If the generated graphical representation does not appear to fit the expected analysis, parameters of the algorithm may be adjusted to improve the statistical analysis of the data.
A number of reporting applications are available to generate reports for a variety of business purposes. Such reports may be utilized to summarize accounting information, report on product sales, etc. Such reporting products may utilize data from a database to generate some of the information within a report. Such data may be requested using a query, such as through SQL or the like, to return the desired data. The reporting applications may then use the returned query result to populate data tables, generate graphs, or the like.